The present invention relates to a fingerprint authentication system, especially a secure registration-free fingerprint authentication method and system based on local features.
With the increasingly popular application of biometrics in real life, more attention has been drawn to security and privacy problems caused thereby. Investigations show that publics' concern about the risk of identity information leakage and thus potential risk of information security have prevented extensive acceptance of the biometrics, especially fingerprint authentication. Theoretically, any biometric system may face a possibility of being attacked. The security of biometric templates is a key factor for preventing such attacks. Therefore, a secure fingerprint authentication system, in which the templates are securely protected from being obtained easily by attackers, is attracting increasing attention.
Fuzzy commitment scheme is a kind of biometric encryption technology capable of protecting both biometric information and user keys. This scheme can protect the biometric templates from being stolen as well as provide a convenient way for key storage. This scheme was proposed by Juels et al. in 1999 (Ari Juels and Martin Wattenberg. A fuzzy commitment scheme. In Proc. 6th ACM Conf. Comput. Commun. Secur., pages 28-36. ACM Press, 1999). It can be applied to all fuzzy information or biometric traits that are in compliance with its requirement regarding Hamming metrics. As hamming metrics is employed, this scheme was initially applied mostly to iris instead of fingerprints represented by minutiae sets. Secure Sketch, a kind of key-generation technology, was proposed by Dodis et al. in 2004 (Yevgeniy Dodis, Leonid Reyzin, and Adam Smith. Fuzzy extractors: How to generate strong keys from biometrics and other noisy data. In Advances in Crypology-Eurocrypt, volume 3027, pages 523-540. Springer-Verlag, 2004). A Fuzzy Extractor was also proposed in this paper, trying to convert random biometric data to stable keys that can be applied in any encryption environment, so as to enable reliable and secure user identity authentication. According to the secure sketch technique, some public information is extracted from the biometrics. This operation can tolerate a certain degree of errors. Once a data similar to the template data is input, the public information can be used to perfectly reconstruct the template data. However, the public information alone is not enough for reconstruction. The Fuzzy Extractor extracts an approximately uniformly-distributed random data R from input biometric data. Then R can be applied as a key to any encryption environment. PinSketch is a typical secure sketch technology which operates in set metric spaces. Wrap-around secure sketch is another kind of secure sketch technology operating in Euclidean space. It was proposed by Golic et al. at 2008 (Golic, J. D.; Baltatu, M.; “Entropy Analysis and New Constructions of Biometric Key Generation Systems,” Information Theory, IEEE Transactions on, vol. 54, no. 5, pp. 2026-2040, May 2008. doi: 10.1109/TIT.2008.920211).
A major factor determining the performance and security of a fingerprint encryption system is the selection of feature. Currently, the minutia, which is the most stable and robust feature of the fingerprint, is adopted in most systems. However, the minutia is a global feature, which needs registration during application. However, the registration in the fingerprint encryption system is still a difficult problem in that: 1) the fingerprint encryption system is aimed to protect the minutiae from leakage, so minutiae information can no longer be used for registration, and other effective features need to be found; 2) it is difficult to detect a stable feature suitable for registration in a fingerprint image, (e.g., the singular point is unstable and can only be used in registration of rigid transformation.)